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Classic Paper: Elkes J, Elkes C. Effect of chlorpromazine on the behavior of chronically overactive psychotic patients. Br Med J. 1954;2(4887):560-5

In 1950, a group of anesthesiologists in France were trying to find new drugs for anesthesia. They tested the newly synthesized drug chlorpromazine on animals (dogs, rodents, and mice) and found that it led to drowsiness and indifference to aversive stimuli.

Since this was the 1950’s, they were able to quickly try it on people as a booster for anesthesia. They found that people who took chlorpromazine did not lose consciousness, but it did have a profound calming effect. Quickly people thought of trying it on patients with psychosis, for which the available treatments were very limited.

This study by Joel Elkes and Charmian Elkes, who were married, was the first to report a placebo-controlled trial on the effect chlorpromazine in psychosis. It appears that the majority of the data collecting and work was done by Charmian, rather than Joel. Screen Shot 2016-04-11 at 8.19.22 PM

They used a classic crossover study design, testing each patient on both chlorpromazine and an inert placebo (although they do not use the word “random”). They used notes written by the doctors and nurses that were blind to the treatment type to decide whether or not the patient had improved.

Of the 23 patients with a type of psychosis in their study, 7 (30%) showed “definite improvement” when they were taking the drug compared to when they were not, 11 (48%) showed “slight improvement,” and 5 (22%) showed “no improvement.”

Other interesting notes from the paper:

  • They describe the effect of chlorpromazine as symptomatic, since the psychosis itself did not abate: “the essentially symptomatic nature of the response has already been stressed, and cannot be overemphasized. Although affect became more subdued, and attitude and behaviour reflected this improvement, the ingrained psychotic thought disorder seemed to be unchanged.”
  • Because of their detailed records, they noted significant weight gain in 9/23 of the patients (in all of whom the drug led to at least a slight improvement), which has been borne out in both chlorpromazine and in the drug class in general: almost all antipsychotics result in weight gain. Of this effect, they say: “For the present we are inclined to attribute this to improved eating habit as the patients became less tense, less preoccupied, or less assaultive; though more direct metabolic effects of the drug cannot be excluded.”
  • They also tried it on 3 patients with senile dementia, all of whom had “no improvement.” This is yet another example of how Alzheimer’s is where drug discovery goes to die.

Notably, the mechanism remained pretty unknown until the mid-1960s, when it was shown that dopamine metabolites correlated with the chlorpromazine dose given to animals. In 1976, Seeman et al. found a nearly perfect correlation (on the log-log scale) between the ability of antipsychotic drugs to displace haloperidol from binding to the dopamine receptor and the clinical dose required for its effect.

Screen Shot 2016-04-24 at 2.47.22 PM

Seeman et al., 1976

Interestingly, you can see in this figure that chloroprazamine actually has one of the less strong dopaminergic affinities and higher doses required for controlling schizophrenia. Despite this, it and its derivatives have on to become some of the most game-changing psychiatric drugs of all time.

References

Shen WW. A history of antipsychotic drug development. Compr Psychiatry. 1999;40(6):407-14.
Elkes J, Elkes C. Effect of chlorpromazine on the behavior of chronically overactive psychotic patients. Br Med J. 1954;2(4887):560-5.
Bak M, Fransen A, Janssen J, Van os J, Drukker M. Almost all antipsychotics result in weight gain: a meta-analysis. PLoS ONE. 2014;9(4):e94112.

Seeman P, Lee T, Chau-wong M, Wong K. Antipsychotic drug doses and neuroleptic/dopamine receptors. Nature. 1976;261(5562):717-9.

Classic Paper: Cade JF. Lithium salts in the treatment of psychotic excitement. Med J Aust 1949; 2:349-352

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some wells in the British Isles were known for their salubrious effects on mental illness; this may have been due to their lithium content

Prior to 1949, treatments for mania were limited. That year, John Cade published a paper showing the usefulness of lithium in treating patients with mania (“psychotic excitement”).

Interestingly enough, the finding was apparently a surprise to Cade. He was studying guinea pigs in order to see whether uric acid added to the convulsive toxicity of urea, but he needed to find a way to make uric acid soluble in water to be able to inject it into the guinea pigs. (Confusingly enough, urea and uric acid have almost nothing to do with one another chemically.)

For this, he used the lithium salt of urate, and was surprised to find that it was protective against the urea-induced convulsions. He then injected lithium carbonate alone into guinea pigs, and noted that after a couple of hours, they became lethargic and unresponsive to stimuli.

Skipping straight from this effect in guinea pigs (not even a disease model!! — this would never be allowed today) to humans, Cade then reports on 10 cases of patients with mania who were successfully treated with lithium, including longitudinal cases of chronic mania where the mania subsided during lithium treatment and recrudesced when lithium was discontinued.

Other interesting aspects of this paper:

  • Cade notes that historically, water from certain wells was associated with improvements in mental illness, and speculates that “it is very likely that their supposed efficacy was a real efficacy and directly proportional to the lithium content of the waters.”
  • Cade notes that lithium treatment “would be much preferred” to what is usually now considered the cruel treatment of prefrontal leucotomy, even though this (1949) was the year that the Nobel prize was awarded for it, and its use continued into the mid-1950s.
  • All of the cases reported on were men between ages 40 and 65 years old, indicating a total lack of evidence for generalization of the effect across more diverse patient populations.

Recent meta-analysis (2013) has shown that antipsychotics are more effective than lithium in the treatment of acute mania (e.g., the standardized mean difference in manic symptoms for haloperidol is -0.56, while for lithium it is -0.37), but lithium is still often used in combination with antipsychotics in the treatment of mania.

Overall, this short paper is among the best I’ve read in terms of scientific puzzle solving, although you could argue that Cade got lucky.

References

Cade JF. Lithium salts in the treatment of psychotic excitement. 1949. Bull World Health Organ. 2000;78(4):518-20.

Cipriani A, Barbui C, Salanti G, et al. Comparative efficacy and acceptability of antimanic drugs in acute mania: a multiple-treatments meta-analysis. Lancet. 2011;378(9799):1306-15.

Doig MT, Heyl MG, Martin DF. Lithium and mental health. J Chem Educ. 1973;50(5):343-5.

In everyday life, your muscles, metabolism, and nervous system work together to ensure that your cerebral blood flow meets the metabolic needs of your various brain regions. So if you are trying to scrutinize an impressionist painting, your body will likely relocate more blood flow to your visual cortex.

Following a stroke, this cerebral blood flow regulation is impaired. But, the degree and spread of the impairment is unknown. To investigate this, Hu et al. measured systemic blood pressure (BP) and used a transcranial doppler to measure cerebral blood flow velocity (BFV) at the same time.

In their model, better regulation of cerebral blood flow corresponds to a sharper phase shift between blood pressure (BP) and cerebral blood flow velocity (BFV). Individuals with the highest score of a 9 on their autoregulation index (ARI) have more regulation than those with the lowest score of 0, which corresponds to no phase shift.

When they compared patients who had experienced MCA infarcts (a common type of stroke) and healthy controls, they found that stroke patients had significantly less phase coupling between blood pressure and cerebral blood flow. This effect was pronounced over a wide range of blood pressure oscillation frequencies.

Given enough time and the right conditions, can the body repair its ability to regulate cerebral blood flow following a stroke? When the researchers examined this, they found no statistically significant difference between the BFV-BP phase difference and time since stroke.

But, that doesn’t mean that there’s a statistically significant lack of difference. So, further longitudinal studies will be needed to help clarify whether, in certain people in certain environments, the brain improves its cerebral regulation following stroke.

Reference

Hu K, Lo M-T, Peng C-K, Liu Y, Novak V (2012) A Nonlinear Dynamic Approach Reveals a Long-Term Stroke Effect on Cerebral Blood Flow Regulation at Multiple Time Scales. PLoS Comput Biol 8(7): e1002601. doi:10.1371/journal.pcbi.1002601

In investigating a crime, to pinpoint the culprit, the saying goes, “follow the money.” In science, the saying is (or at least, should be), “follow the ATP.”

A six month old paper acts as a nice review on this topic. The authors stratify tissue types based on the degree of myelination (none, developing, and adult). This is shown here,

where:

  • action potential use is on voltage-gated Na+/K+-ATPases
  • synapse use is on postsynaptic membrane currents, presynaptic calcium entry, and neurotransmitter/vesicle cycling
  • oligodendrocyte resting potential use is continuous Na+/K+ pumps
  • housekeeping use is on protein/lipid synthesis and intracellular trafficking of molecules/organelles

That’s way more than I would have expected on housekeeping. But by far their most surprising finding is that the cost of maintaining the resting potentials in oligodendrocytes is so large that myelination doesn’t usually save energy on net–it depends on the firing rate of the neuron. That’s a heterodox bomb.

I suppose that myelination not leading to energy saving is weak evidence in favor of it doing something else, aside from speeding up spikes. Like, allowing for plasticity.

Reference

Harris; Atwood (2012). “The Energetics of CNS White Matter”Journal of NeuroscienceDOI:10.1523/JNEUROSCI.3430-11.2012

A nice, basic study looks at how altering the location of inhibition onto a pyramidal cell neurite affects its spiking properties. Their inhibition is meant to mimic the effects of cortical interneurons (e.g., basket cells, Martinotti cells), which project onto pyramidal cells each with their own stereotyped spatial distributions.

Elucidating these basic structure-function relationships will make synapse-level connectomics data more useful to determine the function of interneuron types.

Here’s just one of many examples in their extensive report. When they applied inhibition (GABA) to pyramidal cell dendrites further from the soma than their excitatory signal (laser-based glutamate uncaging), which they called “distal inhibition”, it led to an increased threshold required for a spike to occur. But, it didn’t change the intensity of that spike when it did occur.

In constrast, when they applied inhibition to pyramidal cell dendrites between the excitatory signal and the soma, which they called “on-the-path inhibition”, it both slightly increased the depolarization threshold and reduced the spike heights when they did occur. You can see this all below.

As an example of how this could be used, let’s say that, on the basis of connectomics data, you discover that a certain set of cells send projections to pyramidal cells which are systematically distal to the projections from a different set of cells.

What you can then say is that the former class of cells is acting to increase the depolarization threshold which the latter set of cells needs to exceed in order to induce those pyramidal cells to spike. Pretty cool.

Reference

Jadi M, Polsky A, Schiller J, Mel BW (2012) Location-Dependent Effects of Inhibition on Local Spiking in Pyramidal Neuron Dendrites. PLoS Comput Biol 8(6): e1002550. doi:10.1371/journal.pcbi.1002550

Due to randomness in neurodevelopment, it is an unavoidable constraint on neural morphology that some synapses will be further away from the soma than others.

And due to the vagaries of membrane electrophysiology, membrane potential changes will degrade continuously on their journey to the soma.

So, in the absence of an adjustment mechanism, the potentials of more distant synapses would be more degraded when they reach the soma and have a proportionally smaller impact on whether the neuron should spike.

For certain cell types, evolution would probably like to eliminate this bias (“no ion channel taxation without representation”). But the mechanism by which they might do so is unclear.

A modeling study provides intriguing evidence that hippocampal pyramidal neurons adjust for this via homeostatic scaling of the maximum calcium concentration at synapses following action potential backpropagation.

As you can see below, the authors found a strongly negative correlation between the distance from a spine to the soma and its maximum calcium concentration.

Because distance from the soma and EPSP degradation are correlated, they also found a strongly negative association between the degree to which excitatory potentials attenuate on their journey to the soma and their max calcium concentration.

left = model pyramidal neuron with spines; colored circles = locations of spines demarcated in the scatter plots; path distance = 3d separation from the soma to that spine

The main problem with the model is that if synapses really are in a true “synaptic democracy”, then homeostatic scaling to this feature wouldn’t be strong enough to be the only reason why. Figure 8F simply does not show a distribution of jointly independent variables.

Plus, figure 1H shows that almost all of the variance in peak calcium concentration is for synapses <400 microns from the soma. How would you achieve equality of representation between synapses 400 um and 800 um away?

Still, this is a nice example of a structure-function relationship at the synapse level and is a hypothesis wholly worth testing.

Reference

Sterratt DC, Groen MR, Meredith RM, van Ooyen A (2012) Spine Calcium Transients Induced by Synaptically-Evoked Action Potentials Can Predict Synapse Location and Establish Synaptic Democracy. PLoS Comput Biol 8(6): e1002545. doi:10.1371/journal.pcbi.1002545

1) Scale mismatch between the synapse-synapse level and the kind of description you want to acquire about the nervous system for a particular goal. He argues that the point at which the interesting neural computation works might be at the mesoscale. It might be enough to know the statistics of how nerve cells work at the synapse level if you want to predict behavior.

2) Structure-function relationships are elusive in the nervous system. It’s harder to understand the information that is being propagated to the nervous system because its purpose is so much more nebulous than a typical organ, like a kidney.

3) Computation-substrate relationships are elusive in general. The structure of an information processing machine doesn’t tell you about the processing it performs. For example, you can analyze in finest detail the microprocessor structure in a computer, and it will constrain the possible ways it can act, but it won’t tell you what actual operating system it is using.

Here is a link to the video of Movshon’s opening remarks. He also mentions the good-if-true point that the set of connections of C. elegans is known, but our understanding of its physiology hasn’t “been materially enhanced” by having that connectome.

The rest of the debate was entertaining but not all that vitriolic. Movshon and Seung do not appear to disagree on all that much.

I personally lean towards Seung’s side. This is not so much due to the specifics (many of which can be successfully quibbled with), but rather due to the reference class of genomics, a set of technologies and methods which have proven to be very fruitful and well worth the investment.

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